Endocrinol Metab.  2023 Feb;38(1):129-138. 10.3803/EnM.2022.1609.

Predicting the Risk of Insulin-Requiring Gestational Diabetes before Pregnancy: A Model Generated from a Nationwide Population-Based Cohort Study in Korea

• Lee SH
• Yu J
• Han K
• Lee SW
• You SY
• Kim HS
• Cho JH
• Yoon KH
• Kim MK

• KMID: 2539826
• DOI: http://doi.org/10.3803/EnM.2022.1609

Abstract

Background
The severity of gestational diabetes mellitus (GDM) is associated with adverse pregnancy outcomes. We aimed to generate a risk model for predicting insulin-requiring GDM before pregnancy in Korean women.
Methods
A total of 417,210 women who received a health examination within 52 weeks before pregnancy and delivered between 2011 and 2015 were recruited from the Korean National Health Insurance database. The risk prediction model was created using a sample of 70% of the participants, while the remaining 30% were used for internal validation. Risk scores were assigned based on the hazard ratios for each risk factor in the multivariable Cox proportional hazards regression model. Six risk variables were selected, and a risk nomogram was created to estimate the risk of insulin-requiring GDM.
Results
A total of 2,891 (0.69%) women developed insulin-requiring GDM. Age, body mass index (BMI), current smoking, fasting blood glucose (FBG), total cholesterol, and γ-glutamyl transferase were significant risk factors for insulin-requiring GDM and were incorporated into the risk model. Among the variables, old age, high BMI, and high FBG level were the main contributors to an increased risk of insulin-requiring GDM. The concordance index of the risk model for predicting insulin-requiring GDM was 0.783 (95% confidence interval, 0.766 to 0.799). The validation cohort’s incidence rates for insulin-requiring GDM were consistent with the risk model’s predictions.
Conclusion
A novel risk engine was generated to predict insulin-requiring GDM among Korean women. This model may provide helpful information for identifying high-risk women and enhancing prepregnancy care.

Keyword

Diabetes, gestational; Insulin; Nomograms; Risk

Figure

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  Fig. 1. Predictive value of the risk model represented by the area under the curve (AUC) of receiver operating characteristic (ROC) curve.

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  Fig. 2. A nomogram for the prediction of insulin-requiring gestational diabetes. Each of the six variables was applied with scores from 0 to 100. Each variable corresponds to a specific point by drawing a line straight up to the score axis. The total score, the sum of the scores for each of the six variables at the bottom of the nomogram, ranges from 0 to 335. BMI, body mass index; γ-GTP, γ-glutamyl transferase.

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  Fig. 3. Incidence probability of insulin-requiring gestational diabetes mellitus (GDM) according to the total risk score.

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  Fig. 4. Incidence rate (per 1,000 person-years) based on the decile groups of the total risk score in the development and validation cohorts. The numbers on the x-axis represent the range of the total risk score according to each decile group.

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